Image Classification
PyTorch
Safetensors
Transformers
English
resnet10
feature-extraction
jax-conversion
resnet
hil-serl
Lerobot
vision
custom_code
Instructions to use helper2424/resnet10_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use helper2424/resnet10_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="helper2424/resnet10_test", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("helper2424/resnet10_test", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from helper2424/resnet10_test: direct link, hf CLI and curl.
- Browser
- Download file 368 Bytes
-
https://huggingface.co/helper2424/resnet10_test/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://helper2424/resnet10_test/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/helper2424/resnet10_test/resolve/main/preprocessor_config.json
368 Bytes
| { | |
| "crop_pct": 1, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "do_scale": true, | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_processor_type": "ConvNextImageProcessor", | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "shortest_edge": 128 | |
| } | |
| } | |